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We got close to 50% speedup on A6000 by replacing most of cross attention operations in the U-Net with flash attention
Annotated Implementation: https://nn.labml.ai/diffusion/stable_diffusion/model/unet_attention.html#section-45
Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations/blob/master/labml_nn/diffusion/stable_diffusion/model/unet_attention.py#L192
We used this to speed up our stable diffusion playground: promptart.labml.ai
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Here’s the masters program if anyone was curious
https://www.mitropolitiko.edu.gr/en/programmes-of-study/faculty-of-computing/msc-artificial-intelligence/
Thanks
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By taking a proactive approach to cybersecurity, IT departments can help protect their organizations from the ever-growing number of cyber attacks. Here are nine ways IT departments can do proactive cybersecurity.
The post 9 Ways IT Can Do Proactive Cybersecurity appeared first on Data Science Central.
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The leading cancer mortality globally is Lung Cancer. A key objective for increasing lung cancer survival is discovering the illness early, allowing for the most effective treatment choices. Lung cancer develops from lesions in the bronchial epithelium of the lung mucosa. These bronchial lesions can progress to squamous cell lung cancer and assist in forecasting other lung cancers’ development. As a result, approaches for early diagnosis of bronchial lesions are critical for improving lung cancer patient treatment. Using bronchoscopy to image the airway epithelium during a regular airway exam is a noninvasive technique for clinicians to look for such lesions.
Autofluorescence bronchoscopy is one of the most sensitive advanced bronchoscopic video procedures available today. It can efficiently distinguish growing bronchial lesions from the normal epithelium. Unfortunately, the current standard requires human inspection of an incoming AFB video stream, which is time-consuming and error-prone
Continue reading| Check out the paper and github link
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https://text-generator.io now analyses not just linked images but also any text in them so you can analyse receipts/documents/screenshots etc.
Example: https://text-generator.io/playground?text=Checkout+this+reciept+https%3A%2F%2Fstatic.text-generator.io%2Fstatic%2Fimg%2Fcomputer-invoice.png+%0ATotal+Price%3A+&stop_sequences=&number_of_results=1&max_length=100&max_sentences=1&min_probability=0&top_p=0.9&top_k=40&temperature=0.6&repetition_penalty=1&seed=0
Will be a blog coming soon about it :)
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Editor’s Note: This post has been updated to reflect the XPENG G9 launch. It was originally published in November 2021. You don’t need a private plane to be at the forefront of personal travel. Electric automaker XPENG launched the G9 SUV this week during NVIDIA GTC. The intelligent, software-defined vehicle is built on the high-performance Read article >
The post An Elevated Experience: XPENG Launches G9 EV, Taking Innovation Even Higher with NVIDIA DRIVE Orin appeared first on NVIDIA Blog.
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The massive virtual worlds created by growing numbers of companies and creators could be more easily populated with a diverse array of 3D buildings, vehicles, characters and more — thanks to a new AI model from NVIDIA Research. Trained using only 2D images, NVIDIA GET3D generates 3D shapes with high-fidelity textures and complex geometric details. Read article >
The post World-Class: NVIDIA Research Builds AI Model to Populate Virtual Worlds With 3D Objects, Characters appeared first on NVIDIA Blog.
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This post is co-written by Goktug Cinar, Michael Binder, and Adrian Horvath from Bosch Center for Artificial Intelligence (BCAI). Revenue forecasting is a challenging yet crucial task for strategic business decisions and fiscal planning in most organizations. Often, revenue forecasting is manually performed by financial analysts and is both time consuming and subjective. Such manual […]
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In Part 7.0 of the Transfer Learning series we have discussed about Densenet pre-trained model in depth so in this series we will…
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The product of the industry 4.0 revolution is Internet connectivity, the widespread availability of robust wired and Wi-Fi networks, and…
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CHATBOTS IN BANKING AND FINANCIAL SECTOR: WHAT ARE THE CHALLENGES & OPPORTUNITIES?
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AI Weirdness: the strange side of machine learning
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Would love for this community to check it out and give us your feedback, it's 100% free to use and create an account: https://consensus.app/search/
You can ask any plain English research question and we will use language models to try to find relevant findings in research papers. Here's an example: Does Magnesium help with sleep?
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Hey guys! I ran a few benchmarks on Whisper's runtime and cost-to-run on GCP, so just dropping it here in case it's valuable to anyone!
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The goal of blind face restoration is to recover high-quality images of human faces from their low-quality counterparts that have been degraded for an unknown reason. Some degradation causes could be noise, blur, low-resolution, and compression artifacts. In this work, researchers from the Applied Research Center of the Tencent company propose GFP-GAN, a Generative Facial Prior GAN for real-world blind face restoration. As it is possible to see in Figure 1, the images restored through GFP-GAN reach higher realness and fidelity with fewer artifacts.
Continue reading | Check out the paper and github link.
https://preview.redd.it/vvss7n3lnhp91.png?width=1045&format=png&auto=webp&s=8fd0c5ffae078a9aae3ec978caacc898d050bd1a
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I've learned a lot about AI applications by using other people's Google Colab notebooks.
When OpenAI's Whisper arrived, I created a Google Colab notebook so you can run both the transcription and translation functions of this automatic speech recognition system.
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Hey everyone! I'm sure many of you know that OpenAI released Whisper yesterday- an open source speech recognition model with weights available.
Not sure if this is allowed, but I wrote a guide on how to run Whisper that also provides some benchmarks on accuracy, inference time, and cost. Let me know what you think :)
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Data-centric AI doesn't just stop with cleaning and preparing data for model training - there are rich insights to be gleaned from production data. By analyzing, segmenting, and selectively relabeling your production inference data, you can generate datasets for future model retraining. This talk will show you how you can use human-in-the-loop oversight to generate high-quality, labeled datasets using Label Studio from your prediction data for future model retraining.
Tune in to the Modzy Discord Server today at 12:30 EDT!
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Our planet faces a global extinction crisis. UN Report shows a staggering number of more than a million species feared to be on the path of extinction. The most common reasons for extinction include loss of habitat, poaching, and invasive species. Several wildlife conservation foundations, research scientists, volunteers, and anti-poaching rangers have been working tirelessly […]
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Amazon’s product search engine indexes billions of products, serves hundreds of millions of customers worldwide, and is one of the most heavily used services in the world. The Amazon Search team develops machine learning (ML) technology that powers the Amazon.com search engine and helps customers search effortlessly. To deliver a great customer experience and operate […]
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When it rains, it pours. And this GFN Thursday brings a downpour of news for GeForce NOW members. The Logitech G CLOUD is the latest gaming handheld device to support GeForce NOW, giving members a brand new way to keep the gaming going. But that’s not all: Portal with RTX joins GeForce NOW in November, Read article >
The post Go Hands On: Logitech G CLOUD Launches With Support for GeForce NOW appeared first on NVIDIA Blog.
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Autonomous vehicle sensors require the same rigorous testing and validation as the car itself, and one simulation platform is up to the task. Global tier-1 supplier Continental and software-defined lidar maker AEye announced this week at NVIDIA GTC that they will migrate their intelligent lidar sensor model into NVIDIA DRIVE Sim. The companies are the Read article >
The post Continental and AEye Join NVIDIA DRIVE Sim Sensor Ecosystem, Providing Rich Capabilities for AV Development appeared first on NVIDIA Blog.
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This blog explains step by step method to convert YOLO V7 PyTorch model to TensorFlow lite.
https://vikasojha894.medium.com/converting-yolo-v7-to-tensorflow-lite-for-mobile-deployment-ebc1103e8d1e
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Hi all, I want to present my new JupyterLab extension jupyter_app_launcher (https://github.com/trungleduc/jupyter_app_launcher). It is used to customize the JupyterLab launcher with a simple YAML file.
Demo
Users can add custom entries to the launcher to:
Open a predefined notebook or markdown file.
Render a notebook in dashboard mode
Open a notebook with Voila
Local/remote services like Plotly Dash or Streamlit
A live demo is available at https://mybinder.org/v2/gh/trungleduc/jupyter_app_launcher/main?urlpath=lab
Documentation: https://jupyter-app-launcher.readthedocs.io/
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My co-founder and I, a senior Amazon research scientist and AWS SDE respectively, launched Marqo a little over a week ago - a "tensor search" engine https://github.com/marqo-ai/marqo
Another project doing doing semantic search/dense retrieval. Why??
Semantic search using vectors does an amazing job when we look at sentences, or short paragraphs. Vectors also do well as an implementation for image search. Unfortunately, vector representations for video, long documents and other more complex data types perform poorly.
The reason isn't really to do with embeddings themselves not being good enough. If you asked a human to find the most relevant document to some search query given a list of long documents, an important question comes to mind - do we want the document that on average is most …
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Girl with a pearl earring, Cute Obama creature, Donald Trump, Boris Johnson, Totoro, Hello Kitty
Online demo: https://replicate.com/lambdal/text-to-pokemon
Code and details: https://github.com/LambdaLabsML/examples/tree/main/stable-diffusion-finetuning
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Earlier this year, Amazon Comprehend, a natural language processing (NLP) service that uses machine learning (ML) to discover insights from text, launched the Targeted Sentiment feature. With Targeted Sentiment, you can identify groups of mentions (co-reference groups) corresponding to a single real-world entity or attribute, provide the sentiment associated with each entity mention, and offer […]
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This post was co-written by Marius Cealera, Senior Partner Solutions Architect at AWS, Zdenko Estok, Cloud Architect at Accenture and Sakar Selimcan, Cloud Architect at Accenture. Machine learning (ML) is a high-stakes business priority, with companies spending $306 billion on ML applications in the past 3 years. According to Accenture, companies that scale ML across […]
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Every company, regardless of its size, wants to deliver the best products and services to its customers. To achieve this, companies want to understand industry trends and customer behavior, and optimize internal processes and data analyses on a routine basis. This is a crucial component of a company’s success. A very prominent part of the […]
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Amazon SageMaker Autopilot has added a new training mode that supports model ensembling powered by AutoGluon. Ensemble training mode in Autopilot trains several base models and combines their predictions using model stacking. For datasets less than 100 MB, ensemble training mode builds machine learning (ML) models with high accuracy quickly—up to eight times faster than […]
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As personal transportation becomes electrified and automated, time in the vehicle has begun to resemble that of a living space rather than a mind-numbing commute. Companies are creating innovative ways for drivers and passengers to make the most of this experience, using the flexibility and modularity of NVIDIA DRIVE IX. In-vehicle technology companies Cerence, Smart Read article >
The post Inside AI: NVIDIA DRIVE Ecosystem Creates Pioneering In-Cabin Features With NVIDIA DRIVE IX appeared first on NVIDIA Blog.
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Breakthroughs in centralized, high performance computing aren’t just opening up new functionality for autonomous driving, but for the in-vehicle experience as well. With the introduction of NVIDIA DRIVE Thor, automakers can build unified AI compute platforms that combine advanced driver-assistance systems and in-vehicle infotainment. The centralized NVIDIA DRIVE architecture supports novel features in the vehicle, Read article >
The post HARMAN to Deliver Immersive In-Vehicle Experience With NVIDIA DRIVE IX appeared first on NVIDIA Blog.
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Whether for virtual assistants, transcriptions or contact centers, voice AI services are turning words and conversations into bits and bytes of business magic. At GTC this week, NVIDIA announced new additions to NVIDIA Riva, a GPU-accelerated software development kit for building and deploying speech AI applications. Riva’s pretrained models are now offered in seven languages, Read article >
The post Now You’re Speaking My Language: NVIDIA Riva Sets New Bar for Fully Customizable Speech AI appeared first on NVIDIA Blog.
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Dentists get a bad rap. Dentists also get more people out of more aggravating pain than just about anyone. Which is why the more technology dentists have, the better. Overjet, a member of the NVIDIA Inception program for startups, is moving fast to bring AI to dentists’ offices. On this episode of the NVIDIA AI Read article >
The post A Podcast With Teeth: How Overjet Brings AI to Dentists’ Offices appeared first on NVIDIA Blog.
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By continuously monitoring a patient’s gait speed, the system can assess the condition’s severity between visits to the doctor’s office.
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Mayor’s youth employment program brought local high schoolers to MIT this summer.
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I started my marketing career at the end of the 2000s. At that time, the digital marketing landscape was scarce and full of uncharted…
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I'm curating a list of resources on Online Learning, Multi-Armed Bandits, RL Theory and Online Algorithms at:
https://sudeepraja.github.io/ResourceOnlineLearning/
Please send in your recommendations for helpful resources in these topics and related areas. I'll add resources on RL Theory and Online Algorithms soon.
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Here's a link to the post where we show how to pass model inputs and outputs directly to the model, which can significantly improve latency by bypassing the PCIe bus and and CPU memory entirely.
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https://gretel.ai/synthesize2023
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Website: https://moraluncertainty.mlsafety.org/
ML Systems often make real-world decisions that involve ethical considerations (modulating social media feeds, conversational AI agents or chatbots, etc). As ML systems automate more aspects of our lives, they should be able to identify moral ambiguity so that they are more likely to proceed cautiously or indicate an operator should intervene.
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From predicting how COVID-19 will spread, to anticipating geopolitical conflicts, using ML to help inform decision-makers could have far-reaching positive effects on the world. The objective of this competition is to train a model to answer forecasting questions using publicly available internet data. For more info visit the competition website.
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https://preview.redd.it/xpjae8s6txo91.jpg?width=2669&format=pjpg&auto=webp&s=497aa4aeed9925d40f7aeebb215605320c43eadc
I have collected here [1,2] almost all available solutions and ideas with codes shared by top performers in the past Kaggle competitions. This list gets updated as soon as a new competition finishes. It allows you to search over the Kaggle past competitions solutions and ideas.
Please share it with your friends.
[1] https://github.com/faridrashidi/kaggle-solutions
[2] https://farid.one/kaggle-solutions/
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After playing around with the Stable Diffusion source code a bit, I got the idea to use it for lossy image compression and it works even better than expected. Details and colab source code here:
https://matthias-buehlmann.medium.com/stable-diffusion-based-image-compresssion-6f1f0a399202?source=friends_link&sk=a7fb68522b16d9c48143626c84172366
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I'm curating a list of resources on Online Learning, Multi-Armed Bandits, RL Theory and Online Algorithms at:
https://sudeepraja.github.io/ResourceOnlineLearning/
Please send in your recommendations for helpful resources in these topics and related areas. I'll add resources on RL Theory and Online Algorithms soon.
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I made a Wordle environment and an algorithm for solving. After some time training, you can see it doing something sensible but I think tuning the rewards, environment or algorithm might make it perform better. Happy to take and merge pull requests if you want to work on it! :)
Link: https://github.com/s-sd/wordle-rl
Stars appreciated! ;)
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Amazon SageMaker Data Wrangler reduces the time that it takes to aggregate and prepare data for machine learning (ML) from weeks to minutes in Amazon SageMaker Studio, the first fully integrated development environment (IDE) for ML. With Data Wrangler, you can simplify the process of data preparation and feature engineering, and complete each step of […]
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Pharmaceutical companies seeking approval from regulatory agencies such as the US Food & Drug Administration (FDA) or Japanese Pharmaceuticals and Medical Devices Agency (PMDA) to sell their drugs on the market must submit evidence to prove that their drug is safe and effective for its intended use. A team of physicians, statisticians, chemists, pharmacologists, and […]
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Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. These algorithms and models can be used for both supervised and unsupervised learning. They can process various types of input data, including tabular, […]
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A data platform is an integrated set of technologies that collectively meet an organization’s end-to-end data needs. It enables the acquisition, storage, preparation, delivery, and governance of your data, as well as a security layer for users and applications.
The post Platform Technical Management – Data Engineering View appeared first on Data Science Central.
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The world is becoming increasingly complex - as highlighted in my first article here - but the concern isn’t only about being complex. Considering the ever-increasing speed of the state of complexity, we have entered the age of polycrisis.
The post Living in a Risk Society – Change, Perpetual Crisis, Comprehension, and Policy appeared first on Data Science Central.
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The problem of data violation is one of the most threatening issues of being on the internet. The ambiguity regarding the collection, usage, and sharing of our personal and sensitive information adds to the insecurity experienced by most consumers.
The post How CPRA Will Change the Face of US Businesses appeared first on Data Science Central.
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South Korea’s most popular AI voice assistant, GiGA Genie, converses with 8 million people each day. The AI-powered speaker from telecom company KT can control TVs, offer real-time traffic updates and complete a slew of other home-assistance tasks based on voice commands. It has mastered its conversational skills in the highly complex Korean language thanks Read article >
The post No Hang Ups With Hangul: KT Trains Smart Speakers, Customer Call Centers With NVIDIA AI appeared first on NVIDIA Blog.
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At GTC today, NVIDIA unveiled a number of updates to its DGX portfolio to power new breakthroughs in enterprise AI development. NVIDIA DGX H100 systems are now available for order. These infrastructure building blocks support NVIDIA’s full-stack enterprise AI solutions. With 32 petaflops of performance at FP8 precision, NVIDIA DGX H100 delivers a leap in Read article >
The post New NVIDIA DGX System Software and Infrastructure Solutions Supercharge Enterprise AI appeared first on NVIDIA Blog.
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New cloud services to support AI workflows and the launch of a new generation of GeForce RTX GPUs featured today in NVIDIA CEO Jensen Huang’s GTC keynote, which was packed with new systems, silicon, and software. “Computing is advancing at incredible speeds, the engine propelling this rocket is accelerated computing, and its fuel is AI,” Read article >
The post Keynote Wrap-Up: NVIDIA CEO Unveils Next-Gen RTX GPUs, AI Workflows in the Cloud appeared first on NVIDIA Blog.
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Meet Violet, an AI-powered customer service assistant ready to take your order. Unveiled this week at GTC, Violet is a cloud-based avatar that represents the latest evolution in avatar development through NVIDIA Omniverse Avatar Cloud Engine (ACE), a suite of cloud-native AI microservices that make it easier to build and deploy intelligent virtual assistants and Read article >
The post NVIDIA Omniverse ACE Enables Easier, Faster Deployment of Interactive Avatars appeared first on NVIDIA Blog.
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The latest release of NVIDIA Maxine is paving the way for real-time audio and video communications. Whether for a video conference, a call made to a customer service center, or a live stream, Maxine enables clear communications to enhance virtual interactions. NVIDIA Maxine is a suite of GPU-accelerated AI software development kits (SDKs) and cloud-native Read article >
The post New NVIDIA Maxine Cloud-Native Architecture Delivers Breakthrough Audio and Video Quality at Scale appeared first on NVIDIA Blog.
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Recommender systems, the economic engines of the internet, are getting a new turbocharger: the NVIDIA Grace Hopper Superchip. Every day, recommenders serve up trillions of search results, ads, products, music and news stories to billions of people. They’re among the most important AI models of our time because they’re incredibly effective at finding in the Read article >
The post Why the New NVIDIA Grace Hopper Superchip Is Ideal for Next-Gen Recommender Systems appeared first on NVIDIA Blog.
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Promising to help process images faster and more efficiently at a vast scale, NVIDIA introduced CV-CUDA, an open-source library for building accelerated end-to-end computer vision and image processing pipelines. The majority of internet traffic is video. Increasingly, this video will be augmented by AI special effects and computer graphics. To add to this complexity, fast-growing Read article >
The post NVIDIA Introduces Open-Source Project to Accelerate Computer Vision Cloud Applications appeared first on NVIDIA Blog.
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In her 18 years as a competitive figure skater, Bettina Heim learned to land a lutz with speed and grace. Now, armed with a Ph.D. in quantum computing, she’s helping Microsoft Azure Quantum carve out a position at the cutting edge of cloud services. “I’ve always been attracted to interesting problems and working hard to Read article >
The post Growing Range of Researchers, Scientists Adopt NVIDIA cuQuantum and QODA appeared first on NVIDIA Blog.
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Robotics developers can span global teams testing for navigation of environments, underscoring the importance of easy access to simulation software for quick input and iterations. At GTC today, NVIDIA founder and CEO Jensen Huang announced that the Isaac Sim robotics simulation platform is now available on the cloud. Developers will have three options to access Read article >
The post NVIDIA Robotics Software Jumps to the Cloud, Enabling Collaborative, Accelerated Development of Robots appeared first on NVIDIA Blog.
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Content creation is booming at an unprecedented rate. Whether it’s a 3D artist sculpting a beautiful piece of art or an aspiring influencer editing their next hit TikTok, more than 110 million professional and hobbyist artists worldwide are creating content on laptops and desktops.
The post Creativity Redefined: New GeForce RTX 40 Series GPUs and NVIDIA Studio Updates Accelerate AI Revolution appeared first on NVIDIA Blog.
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NVIDIA today introduced the NVIDIA IGX platform for medical edge AI use cases, bringing advanced security and safety to intelligent machines and human-machine collaboration. IGX is a hardware and software platform that delivers secure, low-latency AI inference to meet the clinical demand for instant insights from a range of devices and sensors for medical applications, Read article >
The post NVIDIA Medical Edge AI Computing Platform Selected by Top Robotic and Digital Surgery Startups appeared first on NVIDIA Blog.
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NVIDIA today introduced the IGX edge AI computing platform for secure, safe autonomous systems. IGX brings together hardware with programmable safety extensions, commercial operating-system support and powerful AI software — enabling organizations to safely and securely deliver AI in support of human-machine collaboration. The all-in-one platform enables next-level safety, security and perception for use cases Read article >
The post New NVIDIA IGX Platform Helps Create Safe, Autonomous Factories of the Future appeared first on NVIDIA Blog.
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Next-day packages. New vehicle deliveries. Fresh organic produce. Each of these modern conveniences is accelerated by fleets of mobile robots. NVIDIA today is announcing updates to Nova Orin — an autonomous mobile robot (AMR) reference platform — that advance its roadmap. We’re releasing details of three reference platform configurations. Two use a single Jetson AGX Read article >
The post NVIDIA Isaac Nova Orin Opens New Era of Innovation for Autonomous Mobile Robots appeared first on NVIDIA Blog.
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Deutsche Bahn’s rail network consists of 5,700 stations and 33,000 kilometers of track, making it the largest in Western Europe. Digitale Schiene Deutschland (Digital Rail for Germany, or DSD), part of Germany’s national railway operator Deutsche Bahn, is working to increase the network’s capacity without building new tracks. It’s striving to create a powerful railway Read article >
The post On Track: Digitale Schiene Deutschland Building Digital Twin of Rail Network in NVIDIA Omniverse appeared first on NVIDIA Blog.
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With tens of millions of weekly transactions across its more than 2,000 stores, Lowe’s helps customers achieve their home-improvement goals. Now, the Fortune 50 retailer is experimenting with high-tech methods to elevate both the associate and customer experience. Using NVIDIA Omniverse Enterprise to visualize and interact with a store’s digital data, Lowe’s is testing digital Read article >
The post Reinventing Retail: Lowe’s Teams With NVIDIA and Magic Leap to Create Interactive Store Digital Twins appeared first on NVIDIA Blog.
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With NVIDIA DRIVE, in-vehicle infotainment, or IVI, is so much more than just giving directions and playing music. NVIDIA founder and CEO Jensen Huang demonstrated the capabilities of a truly IVI experience during today’s GTC keynote. Using centralized, high-performance compute, the NVIDIA DRIVE Concierge platform spans traditional cockpit and cluster capabilities, as well as personalized, Read article >
The post Experience the Future of Vehicle Infotainment: NVIDIA DRIVE Concierge Brings Customized AI to Every Seat appeared first on NVIDIA Blog.
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The next generation of autonomous vehicle computing is improving performance and efficiency at the speed of light. During today’s GTC keynote, NVIDIA founder and CEO Jensen Huang unveiled DRIVE Thor, a superchip of epic proportions. The automotive-grade system-on-a-chip (SoC) is built on the latest CPU and GPU advances to deliver 2,000 teraflops of performance while Read article >
The post NVIDIA DRIVE Thor Strikes AI Performance Balance, Uniting AV and Cockpit on a Single Computer appeared first on NVIDIA Blog.
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Data science assists SEO experts in countless ways, like personalizing the customer experience, understanding client requirements, and many other things.
The post How to Use Data Science for Search Engine Optimization appeared first on Data Science Central.
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Hello! I wanted to share our recent work on understanding & explaining ML models through natural language conversations.
We use dialogues as an accesible tool for model understanding, so anyone can "talk" to an ML model to understand it, like its another colleague. We also provide a flexible implementation you can adapt to your models & datasets.
Twitter thread: https://twitter.com/dylanslack20/status/1571945003676737537
Paper: https://arxiv.org/abs/2207.04154
Code: https://github.com/dylan-slack/TalkToModel
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Yes, you read the title correctly.
This is more of a character study/shitpost testing out Stable Diffusion textual inversion to see how to control it / expected outputs. Turns out, it works better than I thought, and emphasizing/deemphasizing specific terms when using textual inversion works out well.
The post also includes a custom inference notebook for multiple inversion concepts.
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TorchStudio 0.9.10 was just released with extensions for all the major Python IDEs (VS Code, PyCharm, Spyder and Sublime Text) by popular request, looking forward for your comments !
One new tutorial and two new videos describe how to use TorchStudio from within your IDE.
Download: https://www.torchstudio.ai/download/Full changelog: https://github.com/TorchStudio/torchstudio/releases/tag/0.9.10
If you're new to TorchStudio, here's an introductory tutorial and video:
https://www.torchstudio.ai/getstarted/
https://www.youtube.com/watch?v=uvA-ARpKdCA
https://preview.redd.it/21tufwslnto91.png?width=3074&format=png&auto=webp&s=802b954254f44b5a737070b300c029457fe58962
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Video: https://youtu.be/xbxe-x6wvRw
Yannic Kilcher's summary: Stable Diffusion has been released and is riding a wave of creativity and collaboration. But not everyone is happy about this. This video takes a look at the vibrant open-source community around the model, and its critics.
Watch here: https://youtu.be/xbxe-x6wvRw
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I'm trying to do an excersive for my ML class, where I have to do lineal regresion with regularization, with either Lasso or Ridge.
Doing it with an iterative method, updating the weights, I have no idea how to actually do it.
Considering this are the augmented error measurements for Lasso and Ridge, I know I have to calculate the gradient, and (I think?) then the update rule becomes: w_new = w_old - (gradient of E_aug). But I'm not actually sure, and even more so, I wouldn't know how to compute the gradient itself, especially for Lasso.
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Last year, we announced the general availability of RStudio on Amazon SageMaker, the industry’s first fully managed RStudio Workbench integrated development environment (IDE) in the cloud. You can quickly launch the familiar RStudio IDE, and dial up and down the underlying compute resources without interrupting your work, making it easy to build machine learning (ML) […]
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As AI becomes more deeply integrated into every aspect of our lives, it is essential that AI systems perform appropriately for their intended use. We know AI models can never be perfect, so how do we decide when AI performance is ‘good enough’ for use in a real life application? Is level of accuracy a […]
The post AI Models vs. AI Systems: Understanding Units of Performance Assessment appeared first on Microsoft Research.
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There have been startups that have survived, and there have been startups that have failed. However, what makes one startup succeed over…
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This youtuber is using some sort of ai character to talk for him im wondering what the software is called?
https://youtube.com/watch?v=GnVtXYvJveI&feature=share&si=EMSIkaIECMiOmarE6JChQQ
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It has annotated code of stable diffusion model; DDIM and DDPM sampling; and scripts to generate and in-paint.
- Code & notes: https://nn.labml.ai/diffusion/stable_diffusion/index.html
- Github: https://github.com/labmlai/annotated_deep_learning_paper_implementations
- This implementation based on the official implementation : https://github.com/CompVis/stable-diffusion
- We have deployed a server to try stable diffusion here: https://promptart.labml.ai
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In the blog “Why Data Management is Today’s Most Important Business Discipline”, I challenged the business and IT communities to reframe the data management conversation; to transform data management from an IT practice into a business discipline focused on leveraging data (and analytics) to deliver business and operational outcomes.
The post Data Management as a Business Discipline – Part 2: Theorems and Principles appeared first on Data Science Central.
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Algorithmic or automated trading refers to trading based on pre-determined instructions fed to a computer – the computers are programmed to execute buy or sell orders in response to varying market data. It’s a trading strategy widely adopted in the finance industry and still growing. The global algorithmic trading market is predicted to reach $18… Read More »How Algorithmic Trading Companies Automate Their Investment Strategy
The post How Algorithmic Trading Companies Automate Their Investment Strategy appeared first on Data Science Central.
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In this article, let’s discuss how data analysis in investment banking is transforming the way investment banks work, the challenges that they get when engaging in this transformation process, use cases, and more.
The post An Overview of Data Analytics in Investment Banking appeared first on Data Science Central.
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An even more significant challenge involves meeting the electrical demands of coming HPC systems and data centers in a sustainable way. Some exascale systems already have energy requirements akin to an entire town.
The post Making Data Centers More Sustainable appeared first on Data Science Central.
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Utah Governor Spencer J. Cox signed the Utah Consumer Privacy Act (UCPA) into law in March 2022. It has since become only the fourth US state to have its own data protection law after Colorado, Virginia, and California.
The post What Does Utah Consumer Privacy Act Mean for US Businesses? appeared first on Data Science Central.
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I'm trying to build a malicious URL detection algorithm using a hybrid DT and RF for my MSc dissertation and I'm having a bit of trouble implementing Stacking at the end of my code.
It currently works fine when using just DT and RF, but I'm really struggling to add the Stacking at the end for my final output. I've been trying to follow this, but it's not really working out.
You can see my code here and how I've been failing to add Stacking at the bottom.
I think the main area of issue is getting my dataset to work with the Stacking algorithm, I can't seem to translate it.
Can anyone please help me? This is driving me crazy
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Text annotations provide models with a better understanding of the data they are given, allowing them to interpret the text more accurately.
The post Usability of Text Annotation in Machine Learning appeared first on Data Science Central.
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Registration for Microsoft Research Summit is now open! Join us October 18 - 20, 2022 to hear from the global research community on what's next for technology and humanity.
Learn more about Research Summit and register.
https://researchsummit.microsoft.com/?OCID=msr\_researchsummit\_social\_RD\_2022
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Artificial intelligence (AI) is the demonstration of intelligence by machines or computers, and it is often used to derive insights from massive amounts of unstructured data.
Skills in artificial intelligence (AI) and machine learning (ML) are in high demand in the IT sector. Indeed, these innovative tools are reshaping the way firms’ function.
Read more: https://mezkit.com/7-tips-and-tricks-for-starting-career-in-artificial-intelligence-machine-learning/
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Customer relationship management (CRM) is a critical tool that organizations maintain to manage customer interactions and build business relationships. Zendesk is a CRM tool that makes it easy for customers and businesses to keep in sync. Zendesk captures a wealth of customer data, such as support tickets created and updated by customers and service agents, […]
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Amazon SageMaker Automatic Model Tuning introduces Hyperband, a multi-fidelity technique to tune hyperparameters as a faster and more efficient way to find an optimal model. In this post, we show how automatic model tuning with Hyperband can provide faster hyperparameter tuning—up to three times as fast. The benefits of Hyperband Hyperband presents two advantages over […]
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In this post, we demonstrate how to use Amazon Polly—a leading cloud service that converts text into lifelike speech—to read the content of a webpage and highlight the content as it’s being read. Adding audio playback to a webpage improves the accessibility and visitor experience of the page. Audio-enhanced content is more impactful and memorable, […]
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AI has become a buzzword in the business world. As the technology becomes more advanced, it is becoming a necessity for businesses to adopt…
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Does anyone know of any glossolalia data sets? Or perhaps papers that use modern speech models to study glossolalia?
I couldn't find anything on Google Scholar but it might just be too niche a topic. Or maybe I'm using the wrong terms.
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I remember asking a while ago whether it makes sense to run neural nets in an architecture more resembling biological brain, and apparently there are efforts to accomplish exactly that:
https://www.fz-juelich.de/en/news/archive/feature-stories/faster-than-the-biological-model
In particular, this architecture allows to circumvent von Neumann bottleneck, which is manifested in latencies due to separation of memory and processing units in the classical computer architecture, thus resembling human brain more closely.
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Hello,
We are accepting short (4+n) or long paper (8+n) contributions to our workshop, "Behavior-driven Autonomous Driving in Unstructured Environments (BADUE22)", to be held at IROS 2022 in Kyoto, Japan on 27th October 2022. We encourage the submission of early ideas, late-breaking results, position papers, or open research questions that are likely to generate interesting discussions. Work published elsewhere is allowed. Accepted papers will be presented in a poster session and selected papers as spotlight talks. All submitted contributions will go through a single blind review process.
Deadline: Sept. 20, 2022 (AoE).
Website: https://gamma.umd.edu/workshops/badue22/
Submit: https://cmt3.research.microsoft.com/BADUE2022/Submission/Index/
Contact organizer via email: rchandra@utexas.…
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Hi folks,
stylepoint here.
I have uploaded some new videos and posting the news here - maybe people find them helpful (:
Also, some folks who have not seen the previous post might discover this one (:
New vids:
AI/ML Model API Design and Numerical Stability (follow-up)
Implement - Linear Regression
The first one is a follow-up video I have decided to upload in order to make things clear and update some of our model implementations.
I made some further changes based on your and others' feedback and suggestions:
All of the videos on the channel have timestamps now! (so you can skip chapters or just skim over the vids).
I have increased the font size of the terminal so hoping the code is a lot more readable now.
Increased the volume for the new video (should be better moving …
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SpaceRobotEnv is an open-sourced environments for trajectory planning of free-floating space robots. Reaching high-level planning accuracy, bimanual coordination and end-to-end control remains an open challenge for space robotics researchers. To better help the community study this problem, SpaceRobotEnv are developed with the following key features: Real Space Environment; Dynamic coupling control; Image input. URL: https://github.com/Tsinghua-Space-Robot-Learning-Group/SpaceRobotEnv. Note: our repo can be found in the OpenAI Gym Documentation now. Please see SpaceRobotEnv. Hope everyone enjoy it!
https://reddit.com/link/xek9im/video/0migj29dlxn91/player
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Growing up in a military family, Christopher Scott moved more than 30 times, which instilled in him “the ability to be comfortable with, and even motivated by, new environments,” he said.
The post Meet the Omnivore: Christopher Scott Constructs Architectural Designs, Virtual Environments With NVIDIA Omniverse appeared first on NVIDIA Blog.
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As the population ages, there is an increasing need for healthcare services. More people live longer than ever before, so they are likely…
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Amazon SageMaker Studio Lab is a free machine learning (ML) development environment based on open-source JupyterLab for anyone to learn and experiment with ML using AWS ML compute resources. It’s based on the same architecture and user interface as Amazon SageMaker Studio, but with a subset of Studio capabilities. When you begin working on ML […]
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What is THUNET?
A deep learning net/framework named "TsingHua University NET", short for "THUNET", is for non-commercial, educational, scientific purpose for the deep learning community.
How to build a neural network with THUNET?
Next, I will explain how to use THUNET to save and load a model. Models are saved in 7z format, thus gain higher compression rate than zip format by 10%+.Zip / 7zip Compression Differences
Tutorial-3: Model Saving and Loading
Model serialization makes use of the 7z format instead of the legacy zip format for higher compression rate.
Referred from Wiki article on comparison of zip and 7z
In 2011, TopTenReviews found that the 7z compression was at least 17% better than ZIP,[15] and 7-Zip's own site has since 2002 reported that while compression ratio results …
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SpaceRobotEnv is an open-sourced environments for trajectory planning of free-floating space robots. Reaching high-level planning accuracy, bimanual coordination and end-to-end control remains an open challenge for space robotics researchers. To better help the community study this problem, SpaceRobotEnv are developed with the following key features: Real Space Environment; Dynamic coupling control; Image input. URL: https://github.com/Tsinghua-Space-Robot-Learning-Group/SpaceRobotEnv. Note: our repo can be found in the OpenAI Gym Documentation now. Please see SpaceRobotEnv. Hope everyone enjoy it!
https://reddit.com/link/xe3e54/video/u92i2yqg3un91/player
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Amazon Lex is a service for building conversational interfaces using voice and text. Amazon Lex provides high-quality speech recognition and language understanding capabilities. With Amazon Lex, you can add sophisticated, natural language bots to new and existing applications. Amazon Lex reduces multi-platform development efforts, allowing you to easily publish your speech or text chatbots to […]
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Hey everyone, what are your thoughts on this repo? It's essentially a neural search frontend for Opensearch https://github.com/marqo-ai/marqo
Seems quite a cool way to leverage the new kNN functionality painlessly.
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Let’s call it Ai-rt
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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Online trust has come a long way since the time of centralized databases, where information was concentrated in one location and the security and validation of that information relied on a core set of people and systems. While convenient, this model of centralized management and oversight had a number of drawbacks. Trust depended on how […]
The post CCF: Bringing efficiency and usability to a decentralized trust model appeared first on Microsoft Research.
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Today, we are experiencing waves of breakthroughs in computing that are transforming just about every aspect of our lives. Artificial intelligence is changing the way we develop and create. Human language technologies are revolutionizing the workflows of healthcare professionals. Deep learning is accelerating our ability to understand and predict natural phenomena, from atomic to galactic […]
The post Microsoft Research Summit 2022: What’s Next for Technology and Humanity? appeared first on Microsoft Research.
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As consumers expect faster, cheaper deliveries, companies are turning to AI to rethink how they move goods. Foremost among these new systems are “hub-and-spoke,” or middle-mile, operations, where companies place distribution centers closer to retail operations for quicker access to inventory. However, faster delivery is just part of the equation. These systems must also be Read article >
The post Reinventing the Wheel: Gatik’s Apeksha Kumavat Accelerates Autonomous Delivery for Wal-Mart and More appeared first on NVIDIA Blog.
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https://digesttime.com/2022/09/11/elon-musk-spacex-has-had-promising-conversations-with-apple/
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Hi! Just sharing our open-source project to automate MLPerf benchmarks and make it easier for everyone to plug in their real-world ML models, data sets, frameworks/SDKs and hardware. Here is a simple example of a modular image classification to explain the concept. Feedback is very welcome!
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Blockchain is a sophisticated technology. It uses cryptography extensively to secure records and build a tamper-proof network, wherein records can’t be altered unless validated by a majority of participating parties on the network.
The post How Long Does It Take To Learn Blockchain? appeared first on Data Science Central.
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Data accuracy is the biggest challenge many businesses encounter in their quest to cleanse data. Having accurate data is the foundation of the usefulness of data in all its stages of use.
The post Challenges and Best Practices of Data Cleansing appeared first on Data Science Central.
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Advanced data analytics is a driving power nowadays, covering various human activities and giving businesses worthy insights. Having enough analytical data about your enterprise, employees' and customers' satisfaction, finances, and more, project managers can contribute significantly to decision-making, business growth, and overall business prosperity.
The post Project Management Data Analytics: Benefits and Practices appeared first on Data Science Central.
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Natural language understanding, the metaverse and the 3D internet, new gaming technology, and advanced AI technologies impacting industries as varied as transportation, healthcare, finance and entertainment are all coming your way. From advances in robotics to supercomputers and hyperscale data centers, the brightest minds in science, industry and the public sector will discuss the latest Read article >
The post Get up to Speed: Five Reasons Not to Miss NVIDIA CEO Jensen Huang’s GTC Keynote Sept. 20 appeared first on NVIDIA Blog.
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More than 6 million pairs of eyes will be on real-time AI avatar technology in this week’s finale of America’s Got Talent — currently the second-most popular primetime TV show in the U.S.. Metaphysic, a member of the NVIDIA Inception global network of technology startups, is one of 11 acts competing for $1 million and Read article >
The post AI on the Stars: Hyperrealistic Avatars Propel Startup to ‘America’s Got Talent’ Finals appeared first on NVIDIA Blog.
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The gripping sci-fi comic Huxley was brought to life in an action-packed 3D trailer full of excitement and intrigue this week In the NVIDIA Studio.
The post Concept Designer Ben Mauro Delivers Epic 3D Trailer ‘Huxley’ This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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“85% of buyers trust online reviews as much as a personal recommendation” – Gartner Consumers are increasingly engaging with businesses through digital surfaces and multiple touchpoints. Statistics show that the majority of shoppers use reviews to determine what products to buy and which services to use. As per Spiegel Research Centre, the purchase likelihood for […]
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Amazon SageMaker Studio is the first fully integrated development environment (IDE) for machine learning (ML). It provides a single, web-based visual interface where you can perform all ML development steps, including preparing data and building, training, and deploying models. AWS Glue is a serverless data integration service that makes it easy to discover, prepare, and […]
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From healthcare and manufacturing to marketing and engineering, we are still seeing nearly five different generations share the workforce…
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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Artificial intelligence has gained huge popularity in the last few years, with its application surging across every business sector. AI has impressively gained massive acceptance in the mobile tech world by bringing diverse facilities to our fingertips.
The post How AI/ML will Impact iOS App Development in 2023 appeared first on Data Science Central.
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Let's look at this story in more detail because in my view, it shows something much more fundamental which is often overlooked. In my view, the future of all jobs will be in collaborating with AI !
The post Art and AI: The Line Blurs Further appeared first on Data Science Central.
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Register free for NVIDIA GTC to learn from experts on how AI and the evolution of the 3D internet are profoundly impacting industries—and society as a whole. We have prepared several AWS sessions to give you guidance on how to use AWS services powered by NVIDIA technology to meet your goals. Amazon Elastic Compute Cloud […]
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This post is co-written with Rajnish Jain, Priyanka Kulkarni and Daniel Johnson from Medidata. Medidata is leading the digital transformation of life sciences, creating hope for millions of patients. Medidata helps generate the evidence and insights to help pharmaceutical, biotech, medical devices, and diagnostics companies as well as academic researchers with accelerating value, minimizing risk, […]
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https://lambdalabs.com/blog/multi-node-pytorch-distributed-training-guide/
This is a step-by-step guide that:
Walks you through how to scale your PyTorch training across multiple nodes.
Provides examples that showcase the boilerplate of PyTorch DDP training code.
Shows you how to launch applications using PyTorch’s distributed.launch and torchrun methods, as well as Open MPI’s mpirun method.
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I was learning the masked language modeling codebase in Huggingface Transformers. Just a question to understand the language model head.
Here at the final linear layer where we project hidden size to vocab size (https://github.com/huggingface/transformers/blob/f2fbe4475386bfcfb3b83d0a3223ba216a3c3a91/src/transformers/models/bert/modeling_bert.py#L685-L702).
python3 self.decoder = nn.Linear(config.hidden_size, config.vocab_size, bias=False) self.bias = nn.Parameter(torch.zeros(config.vocab_size)) self.decoder.bias = self.bias We set the bias term to zero at the moment. And later when we initialize the weight, we tie the weight of the linear layer and the word embedding.
But we don't do such a thing for the bias term. I wonder how we can understand that and why we want to initialize the …
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A few weeks ago, before stable-diffusion was officially released, I found that fine-tuning Dalle-mini's VQGAN decoder can improve the performance on anime images. See:
https://preview.redd.it/eekf9hjt3gn91.png?width=1280&format=png&auto=webp&s=25938a4ad284e6cfff958ad0d69968cd2c01ed18
And with a few lines of code change, I was able to train the stable-diffusion VAE decoder. See:
https://preview.redd.it/45xogflo5gn91.png?width=1129&format=png&auto=webp&s=43f98e863b918bba9d7471a0cfa7de4dcc8df98c
You can find the exact training code used in this repo: https://github.com/cccntu/fine-tune-models/
More details about the models are also in the repo.
And you can play with the former model at https://github.com/cccntu/anim_e
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I've built a library to explore machine learning with functional programming and dependent types, including statically-verified shapes like transpose : Tensor [m, n] dtype -> Tensor [n, m] dtype It compiles with XLA, and shares a similar approach to JAX and Dex.
I've made significant progress since my post last December: I've implemented much of the linear algebra API, and it now runs on GPU. I next want autodiff, gradient descent and vectorized map (a la JAX's vmap). I've started work on these but there's still much to do.
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I am looking at this repo:
https://github.com/marlbenchmark/on-policy/blob/af4dc22aaf05b281d9e2e4f43c9ebb9eca48137e/onpolicy/runner/separated/mpe_runner.py#L67
And I am wondering: how do you compute rewards when you have multiple parallel environments? Do you take an average? I don't see any reference here to multiple rollout threads, so what happens when you do have some?
Thanks!
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Fast.ai is a revolutionary library created by Jeremy Howard who was a former Kaggle no 1 Grandmaster. He has developed the Fast.ai course…
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I conducted a small research to see how recent developments in AI will affect the comic book industry.
I’ve run two experiments one with Dall-E and anotherone with Midjourney (Stable Diffusion is on it’s way). In both examples, I used a script of Killing Joke by Alan Moore and and compared it with original.
Dall-E Experiment
Midjourney Experiment
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https://youtu.be/db0uUa5_cTE
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Hi there, I've uploaded a notebook file where you can test out the newest pytorch jit compile feature that works with Stable diffusion to further accelerate the inference time!
https://github.com/cloneofsimo/sd-various-ideas/blob/main/create_jit.ipynb This lets you create jit with Stable diffusion v1.4
https://github.com/cloneofsimo/sd-various-ideas/blob/main/inference_nvFuserJIT.ipynb This lets you use the jit compiled SD model to accelerate the sampling algorithm.
Currently only has DDIM implementation. I hope this helps for someone who is working with stable diffusions to further accelerate them or anyone interested in jit, nvFuser in general.
On single 512 x 512 image, 50 DDIM steps, it takes 3.0 seconds!
Im implementing various ideas (such as blended latent diffusion) with SD on this repo, https://github.com/cloneofsimo/sd-various-ideas , so give it a star if you find it helpful!
Output from AMP + nvFuser
https://preview.redd.it/pwtpex6diwm91.png?width=700&format=png&auto=webp&s=3d856529b2c4949a9359adaa8e41f5d12e98c64f
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Hi, wanted to shared some of the work we have been up to on the side of ML for olfaction.
Google AI Blogpost, which introduces three works:
A Principal Odor Map Unifies Diverse Tasks in Human Olfactory Perception
Metabolic activity organizes olfactory representations
A deep learning and digital archaeology approach for mosquito repellent discovery
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The aphorism acknowledges that models of our knowledge always fall short of the complexities of reality but can still be useful nonetheless. With this model background, let us delve into this article focusing on specific technical debt in Machine Learning System development.
The post Technical Debt In Machine Learning System – A Model Driven Perspective appeared first on Data Science Central.
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The last few years have seen rapid development in the field of natural language processing (NLP). Although hardware has improved, such as with the latest generation of accelerators from NVIDIA and Amazon, advanced machine learning (ML) practitioners still regularly encounter issues deploying their large language models. Today, we announce new capabilities in Amazon SageMaker that […]
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In this post, we discuss best practices to improve the performance of your computer vision models using Amazon Rekognition Custom Labels. Rekognition Custom Labels is a fully managed service to build custom computer vision models for image classification and object detection use cases. Rekognition Custom Labels builds off of the pre-trained models in Amazon Rekognition, which […]
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To train a machine learning (ML) model, you need a large, high-quality, labeled dataset. Amazon SageMaker Ground Truth helps you build high-quality training datasets for your ML models. With Ground Truth, you can use workers from either Amazon Mechanical Turk, a vendor company of your choosing, or an internal, private workforce to enable you to […]
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Amp is a new live radio app from Amazon. With Amp, you can host your own radio show and play songs from the Amazon Music catalog, or tune in and listen to shows other Amp users are hosting. In an environment where content is plentiful and diverse, it’s important to tailor the user experience to […]
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Amp, the new live radio app from Amazon, is a reinvention of radio featuring human-curated live audio shows. It’s designed to provide a seamless customer experience to listeners and creators by debuting interactive live audio shows from your favorite artists, radio DJs, podcasters, and friends. However, as a new product in a new space for […]
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This is a guest blog post cowritten with athenahealth. athenahealth a leading provider of network-enabled software and services for medical groups and health systems nationwide. Its electronic health records, revenue cycle management, and patient engagement tools allow anytime, anywhere access, driving better financial outcomes for its customers and enabling its provider customers to deliver better quality […]
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For a couple of years now I've been using neural networks to generate daily drawing prompts. With today's text-generating neural networks far too large to finetune on a list of existing prompts, I've turned to other methods. One method that works surprisingly well is
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AI Weirdness: the strange side of machine learning
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Content Moderation means the moderation of the user-generated content which is getting published on various online platforms. The term…
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Hey all,
We have compiled a Reddit post and comment dataset for your analysis. It aims to contain all climate change discussion on Reddit in a set of CSV files - hopefully helping bridge real world problems with solutions based on online community data. You can use it to analyze misinformation, track trends, and many more (data science is an open field!)
You can download it here. Or here, if you are using Huggingface Datasets.
Enjoy!
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Release notes available here: https://github.com/openai/gym/releases/tag/0.26.0
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In their debut on the MLPerf industry-standard AI benchmarks, NVIDIA H100 Tensor Core GPUs set world records in inference on all workloads, delivering up to 4.5x more performance than previous-generation GPUs. The results demonstrate that Hopper is the premium choice for users who demand utmost performance on advanced AI models. Additionally, NVIDIA A100 Tensor Core Read article >
The post NVIDIA Hopper Sweeps AI Inference Benchmarks in MLPerf Debut appeared first on NVIDIA Blog.
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This GFN Thursday marks a milestone: With the addition of six new titles this week, more than 1,400 games are now available to stream from the GeForce NOW library. Plus, GeForce NOW members streaming to supported Smart TVs from Samsung and LG can get into their games faster with an improved user interface. Your Games, Read article >
The post GeForce NOW Supports Over 1,400 Games Streaming Instantly appeared first on NVIDIA Blog.
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Researchers develop a new method that uses multiple models to create more complex images with better understanding.
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Stable Diffusion web UI
A browser interface based on Gradio library for Stable Diffusion.
github: https://github.com/AUTOMATIC1111/stable-diffusion-webui
https://preview.redd.it/7vk3oijorim91.png?width=1594&format=png&auto=webp&s=8e6096c86b95ed1ed338b9501e2b5c586164d0e9
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I’ve been looking for an AI generator that can create something like this. It sort of creates an image similar to the base image and then keeps going, making more that copy off themselves. Anyone have any examples of programs that can do this?
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Amazon SageMaker provides a suite of built-in algorithms, pre-trained models, and pre-built solution templates to help data scientists and machine learning (ML) practitioners get started on training and deploying ML models quickly. You can use these algorithms and models for both supervised and unsupervised learning. They can process various types of input data, including tabular, […]
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Many AWS customers have been successfully using Amazon Transcribe to accurately, efficiently, and automatically convert their customer audio conversations to text, and extract actionable insights from them. These insights can help you continuously enhance the processes and products that directly improve the quality and experience for your customers. In many countries, such as India, English […]
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Despite increasingly widespread use of machine learning (ML) in all aspects of our lives, a broad class of scenarios still rely on automation designed by people, not artificial intelligence (AI). In real-world applications that involve making sequences of decisions with long-term consequences, from allocating beds in an intensive-care unit to controlling robots, decision-making strategies to […]
The post A game-theoretic approach to provably correct and scalable offline RL appeared first on Microsoft Research.
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Drupal is an open-source content management system that powers hundred of thousands of websites particularly high-traffic ones. It’s especially popular among professional developer for its adaptability and government website for its high level of security. In this piece, we’ll discuss why you might want to select Drupal, who Drupal is right for, and how to… Read More »6 Reasons Why You Need to Integrate Your Drupal Hosting With Cloudways
The post 6 Reasons Why You Need to Integrate Your Drupal Hosting With Cloudways appeared first on Data Science Central.
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Researchers increase the accuracy and efficiency of a machine-learning method that safeguards user data.
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Optimized Stable Diffusion
This repo is a modified version of the Stable Diffusion repo, optimized to use less VRAM than the original by sacrificing inference speed.
To achieve this, the stable diffusion model is fragmented into four parts which are sent to the GPU only when needed. After the calculation is done, they are moved back to the CPU. This allows us to run a bigger model while requiring less VRAM.
github: https://github.com/neonsecret/stable-diffusion
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An interview with Brenden Bartholomew, President of Vector Aerial, on the use of drones in both military and civilian contexts, as well as a discussion about how Drone AI works and where it's heading
The post The Cagle Report – Episode 1 – Send in the Drones appeared first on Data Science Central.
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When most people think of using machine learning (ML) with audio data, the use case that usually comes to mind is transcription, also known as speech-to-text. However, there are other useful applications, including using ML to detect sounds. Using software to detect a sound is called audio event detection, and it has a number of […]
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Like two valedictorians, SimInsights and Photomath tell stories worth hearing about how AI is advancing education. SimInsights in Irvine, Calif., uses NVIDIA conversational AI to make virtual and augmented reality classes lifelike for college students and employee training. Photomath — founded in Zagreb, Croatia and based in San Mateo, Calif. — created an app using Read article >
The post Model Teachers: Startups Make Schools Smarter With Machine Learning appeared first on NVIDIA Blog.
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Viral creator turned NVIDIA 3D artist Lorenzo Drago takes viewers on a jaw-dropping journey through Toyama, Japan’s Etchū-Daimon Station this week In the NVIDIA Studio.
The post Ridiculously Realistic Renders Rule This Week ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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Data Science is a popular term nowadays. In fact, it’s one of the most sought-after jobs in the world. It can be applied to several fields…
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Study finds computer models that predict molecular interactions need improvement before they can help identify drug mechanisms of action.
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I'm not in this field but I'm very interested in being up to date with the latest, weekly and even daily, all things AI. The only two I know is 2 Minute Papers and Dr Alan D. Thompson.
I may have seen others but were very low quality (sensationalism).
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Hey folks! I am just overwhelmed that my AI project was selected by Arm for their upcoming AI Tech Talk. I will present my solution for farmers that helps them avoid fake poor-quality agrochemicals on Sep 20th, at 8:00 AM PT. This is my first webinar of such scale and I would appreciate if you support my project by joining me: https://armltd.zoom.us/webinar/register/4016582497950/WN_fJE_6UT_Q1GCfygq8Ll4tw
Hope to see you!
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Code: https://github.com/gordicaleksa/stable_diffusion_playground
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Justin Pinkey has been experimenting with fine-tuning stable diffusion to use CLIP image embedding as the conditioning instead of a text prompt. This allows you do do the dalle2 like "image variations"
tweet: https://twitter.com/Buntworthy/status/1566744186153484288
github: https://github.com/justinpinkney/stable-diffusion
demo made with gradio: https://github.com/gradio-app/gradio
https://preview.redd.it/9jbdu4n1g2m91.jpg?width=3294&format=pjpg&auto=webp&s=716de69799bf14dcb2b84461f21832b679406e22
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I am training some generative models and need to showcase the generated images.
1) The images I will show when clicked should have related images from the dataset to show their similarity. Much like https://www.robots.ox.ac.uk/~vgg/software/vise/index.html
2) I also want to allow the users to input images and generate a sample using that.
I know there are some tools like Gradio. Are there any other tools available for this purpose?
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In the past few years, blockchain technology has turned out to be a phenomenal technology. The novel attributes of blockchain technology are making business processes more efficient, more secure, and more transparent and are taking the industry toward a new ‘decentralized’ direction.
The post Learn Blockchain Technology to Build A Futuristic Career appeared first on Data Science Central.
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SVG is an example of one of the more powerful technologies on the web that is likely completely invisible to you, whether you're simply browsing on the web or you're a web developer wanting to take advantage of your full toolset.
The post Imaging the Web With Scalable Vector Graphics appeared first on Data Science Central.
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Cancer is partially a developmental illness, with malignancies named for the cell or tissue from which they originate. However, there is no systematic atlas of tumor sources. Identifying a patient’s precise type of cancer and its main site is the first step in deciding on the best course of treatment.
Despite extensive testing, the source of cancer cannot be determined in many situations. Oncologists must employ non-targeted medicines with severe side effects and poor survival rates.
Researchers at Massachusetts General Hospital (MGH) and the Koch Institute for Integrative Cancer Research at MIT may help classify cancers of unknown primary. Their work introduces a new deep learning method by closely examining the gene expression patterns related to early cell development and differentiation.
Continue reading | Check out the paper
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Blockchain technology has outgrown from being distributed ledger in financial applications to peer‐to‐peer networks that hold tremendous value in any industry and sector. Bewildering as the growth has been, organizations are engineering their blockchain.
The post Lack of Trust Continues to Erode Blockchain Adoption appeared first on Data Science Central.
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End-user experience monitoring (EUEM) enables IT professionals to understand issues from the viewpoint of end users, deliver a better customer experience, and fix issues more quickly by constantly capturing failures, breakdowns, page load data, network requests, and other metrics.
The post What is Digital Experience Monitoring (DEM)? appeared first on Data Science Central.
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What is CDN, does it endanger the sensitive data of internet users, and how can companies prevent hackers from exploiting its flaws?
The post CDN: Does Our Need For Internet Speed Put Sensitive Data at Risk? appeared first on Data Science Central.
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Iterating through HTML tables can be tricky, so we've created this simple guide to help you understand how to use Python to extract tabular data from public HTML tables.
The post How to Use Python to Loop Through HTML Tables and Scrape Tabular Data appeared first on Data Science Central.
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Data-centric architecture revisits architecture and turns that architecture on its head. Ever since the dawn of client-server computing, applications have been the focus of enterprise IT buyers.
The post What’s Data-Centric Architecture? appeared first on Data Science Central.
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Blockchain has a chequered history.
The post The AI Vegan – A real use case for NFT/ Blockchain? appeared first on Data Science Central.
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In today’s data-driven economy, any business needs to make sure that their data is easily recoverable and secured in an emergency. The National Archives and Records Administration suggests that close to 93% of the organizations which witness downtime and data loss for over ten and more days can file bankruptcy in a year. No wonder… Read More »Reaping the Benefits of Having a Data Backup and Recovery Plan
The post Reaping the Benefits of Having a Data Backup and Recovery Plan appeared first on Data Science Central.
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Alongside the explosion in enterprise data analytics is the growing realisation that insights, without action, are not enough.
The post Data Storytelling: Meshing Narrative Techniques with Data Science Smarts appeared first on Data Science Central.
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Businesses, whether big or small, know that understanding data is essential to making informed decisions that impact the organization’s bottom line.
The post Reengineer Business Decisions Granularly with Automated Data Collection appeared first on Data Science Central.
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Hi there,
I have set up a basic implementation for Dual Numbers in Python that can be used for automatic differentiation. Here is an example that is also part of the repository:
Gradient descent with dual numbers.
The implementation is pretty simple and therefore easy to understand.
https://github.com/kaifishr/PyDualNumber
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The dataset is geared towards computer vision-powered motorcycle helmets or other inventive avenues.
Get the dataset here: https://www.kaggle.com/datasets/sadhliroomyprime/motorcycle-night-ride-semantic-segmentation
Six standard classes are used which are: Undrivable, Road, Lanemark, My bike, Rider, Movable
Movable denotes moving objects e.g. vehicles, people etc., undrivable denoting areas where one cannot ride to. Other classes are self-explanatory inclusive of road, lanemark (inclusive of reflectors), rider, and, of course, the bike itself.
We have used SuperAnnotate’s pixel editor as the tool for the semantic segmentation. It works on a raster logic as opposed to a vector one. Exporting include the COCO format. We have prepackaged the dataset inclusive of fused images.
Dataset is created by Acme AI Ltd. (www.acmeai.tech) and is #openaccess 😊 😊. Use it to your heart's content.
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https://youtu.be/2ethDz9KnLk
Did you know that something as simple as loading a model can execute arbitrary code on your machine?
Try the model: https://huggingface.co/ykilcher/totally-harmless-model
Get the code: https://github.com/yk/patch-torch-save
OUTLINE:
0:00 - Introduction
1:10 - Sponsor: Weights & Biases
3:20 - How Hugging Face models are loaded
5:30 - From PyTorch to pickle
7:10 - Understanding how pickle saves data
13:00 - Executing arbitrary code
15:05 - The final code
17:25 - How can you protect yourself?
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this video shows you how you can install stable-diffuison on almost any computer regardless of your graphics card and use an easy to navigate website for your creations. It renders slowly but it works.
video: https://www.youtube.com/watch?v=iwHfsDTD8U0
github repo: https://github.com/darkhemic/stable-diffusion-cpuonly
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This is a guest post by Ramzi Alqrainy, Chief Technology Officer, The Chefz. The Chefz is a Saudi-based online food delivery startup, founded in 2016. At the core of The Chefz’s business model is enabling its customers to order food and sweets from top elite restaurants, bakeries, and chocolate shops. In this post, we explain […]
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Distributed deep learning model training is becoming increasingly important as data sizes are growing in many industries. Many applications in computer vision and natural language processing now require training of deep learning models, which are growing exponentially in complexity and are often trained with hundreds of terabytes of data. It then becomes important to use […]
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As a writer, you know the importance of creating high-quality content. Not only does quality content help your website or blog stand out…
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AI Weirdness: the strange side of machine learning
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Hi, this talk looks like another good example of how we can help prevent climate change.
It looks like there are 25 other amazing talks too at PyBay2022, happening in-person in San Francisco AND ONLINE, NEXT SATURDAY Sept 10.
https://pybay.com/talklist/
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What do you all think?
Is the solution of keeping it all for internal use, like Imagen, or having a controlled API like Dall-E 2 a better solution?
Source: https://twitter.com/negar_rz/status/1565089741808500736
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Hey folks! I am just overwhelmed that my AI project was selected by Arm for their upcoming AI Tech Talk. I will present my solution for farmers that helps them avoid fake poor-quality agrochemicals on Sep 20th, at 8:00 AM PT. This is my first webinar of such scale and I would appreciate if you support my project by joining me: https://armltd.zoom.us/webinar/register/4016582497950/WN_fJE_6UT_Q1GCfygq8Ll4tw
Hope to see you!
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Excellent case study regarding the collection and processing of large amounts of data while complying with GDPR in the autonomous driving industry: https://www.youtube.com/watch?v=DPeqEeSKTYA&t=22s
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A new model that maps developmental pathways to tumor cells may unlock the identity of cancers of unknown primary.
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This month’s NVIDIA GTC provides the best opportunity yet to learn how leading companies and their designers, planners and operators are using the industrial metaverse to create physically accurate, perfectly synchronized, AI-enabled digital twins. The global conference, which runs online Sept. 19-22, will focus in part on how NVIDIA Omniverse Enterprise enables companies to design Read article >
The post NVIDIA GTC Dives Into the Industrial Metaverse, Digital Twins appeared first on NVIDIA Blog.
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We’d wake you up when September ends, but then you’d miss out on a whole new set of games coming to GeForce NOW. Gear up for 22 games joining the GeForce NOW library, with 19 day-and-date releases including action role-playing game Steelrising. Playing them all will take some serious strategy. And build the perfect Minifigure Read article >
The post GFN Thursday Slides Into September With 22 New Games appeared first on NVIDIA Blog.
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Bias detection in data and model outcomes is a fundamental requirement for building responsible artificial intelligence (AI) and machine learning (ML) models. Unfortunately, detecting bias isn’t an easy task for the vast majority of practitioners due to the large number of ways in which it can be measured and different factors that can contribute to […]
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dataset
I have an issue with the number of instances:
only one mask
https://dip4fish.blogspot.com/2022/09/train-and-prediction-with-lightning.html
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Show your visualizations in a web based layout using plotly Dash
Continue reading on Becoming Human: Artificial Intelligence Magazine »
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Here's a link to the post discussing this topic - https://exafunction.com/blog/are-gpus-worth-it
At Exafunction, we've noticed a lot of companies CPUs for machine learning inference workloads. We wrote this post to add some color on this and explain why generally GPUs, if managed properly, are the right hardware for these workloads.
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Hey everyone, today I published 1st video regarding "How you can perform neural Architecture Search without training". Do checkout the video. https://www.youtube.com/watch?v=5Iw9pPdXPzI
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NVIDIA is collaborating with the United Nations Economic Commission for Africa (UNECA) to equip governments and developer communities in 10 nations with data science training and technology to support more informed policymaking and accelerate how resources are allocated. The initiative will empower the countries’ national statistical offices — agencies that handle population censuses data, economic Read article >
The post UN Economic Commission for Africa Engages NVIDIA to Boost Data Science in 10 Nations appeared first on NVIDIA Blog.
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In the NVIDIA Studio celebrates the Open Broadcaster Software (OBS) Studio’s 10th anniversary and its 28.0 software release. Plus, popular streamer WATCHHOLLIE shares how she uses OBS and a GeForce RTX 3080 GPU in a single-PC setup to elevate her livestreams.
The post OBS Studio to Release Software Update 28.0 With NVIDIA Broadcast Features ‘In the NVIDIA Studio’ appeared first on NVIDIA Blog.
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Data is the fuel that makes artificial intelligence run. Training machine learning and AI systems requires data. And the quality of datasets has a big impact on the systems’ results. But compiling quality real-world data for AI and ML can be difficult and expensive. That’s where synthetic data comes in. The guest for this week’s Read article >
The post Rendered.ai Founder and CEO Nathan Kundtz on Using AI to Build Better AI appeared first on NVIDIA Blog.
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Happy to share that our study on designing DNA sequences to control gene expression using generative deep learning is just out!
https://www.nature.com/articles/s41467-022-32818-8
This is a continuation of our previous work, where we learned to 'read' regulatory DNA using deep neural nets, accurately predicting gene expression levels in multiple organisms and finding predictive regulatory grammar across whole gene regulatory regions.
https://www.nature.com/articles/s41467-020-19921-4
Here we combine the predictive models with advanced generative models in an architecture termed ExpressionGAN that can be used to 'write' (design) de novo regulatory DNA with target gene expression levels.
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One of the central concepts of the metaverse is the notion that every person has a single sign-on controlled by the vendors, which can, in turn, be used to track users as they move from one virtual world to another.
The post DSC Weekly 30 August 2022 – Metaverse Misfires appeared first on Data Science Central.
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Webby data architects and modelers–the spider-like ones who use intelligent graph design and a bit of glue or another sticky substance to achieve their objectives–are focused on making joinery much more efficient and scaling a lot more useful with the help of more contextualized data.
The post Semantic Graph as the Next Step for Web Data Architecture appeared first on Data Science Central.
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This article is intended to users relying on machine learning solutions offered by third party vendors. It applies to platforms, dashboards, traditional software, or even external pieces of code that are too time consuming to modify. One of the goals is to turn such systems into explainable AI.
The post How to Make Black-box Systems more Transparent appeared first on Data Science Central.
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Technical Debt describes what results when development teams take conscious actions to expedite the delivery of a piece of functionality or a project which later needs to be remediated via refactoring.
The post A Model For Technical Debt In Machine Learning Systems appeared first on Data Science Central.
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The PyTorch team recently released a Deep Learning Compiler for NVIDIA GPUs called nvFuser. This compiler automatically creates quick, adaptable kernels, speeding up user networks. Creating quick bespoke “fusion” kernels at runtime also significantly accelerates deep learning networks running on Volta and later CUDA accelerators. The new and updated compiler, nvFuser, supports a variety of network architectures as well as applications with dynamic inputs of different shapes and strides and has been specially created to address the particular needs of the PyTorch community. In order to optimize and accelerate PyTorch operations, nvFuser uses graphical representations. Users’ PyTorch operations are not directly accessible as a complete program that a system like nvFuser can optimize because PyTorch uses an eager execution approach. As a result, there is a need for intermediary systems that can translate user programs into a format that nvFuser can optimize. These more advanced methods send the captured operations to nvFuser, which can subsequently tailor the user’s script execution for NVIDIA GPUs.
Continue reading |Github link | Reference article
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Reinventing enterprise computing for the modern era, VMware CEO Raghu Raghuram Tuesday announced the availability of the VMware vSphere 8 enterprise workload platform running on NVIDIA DPUs, or data processing units, an initiative formerly known as Project Monterey. Placing the announcement in context, Raghuram and NVIDIA founder and CEO Jensen Huang discussed how running VMware Read article >
The post NVIDIA and VMware CEOs Discuss New Era of Enterprise Computing appeared first on NVIDIA Blog.
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With personalized content more likely to drive customer engagement, businesses continuously seek to provide tailored content based on their customer’s profile and behavior. Recommendation systems in particular seek to predict the preference an end-user would give to an item. Some common use cases include product recommendations on online retail stores, personalizing newsletters, generating music playlist […]
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On its own, a new machine-learning model discovers linguistic rules that often match up with those created by human experts.
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https://github.com/JoaoLages/diffusers-interpret
Looking for contributors to improve this package!
Generated image for the phrase \"A cute corgi with the Eiffel Tower in the background\"
Word importances for the selected region
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https://www.serkansulun.com/midi/
Here is my recent research project. The website has music samples, and links to the paper and the code. It allows conditioning on an arbitrary emotions, using valence-arousal values, and generates 5-instrument (strings, guitar, bass, piano, drums) rock and pop songs. I hope you find it useful.
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Vanessa Rosa’s art transcends time: it merges traditional and contemporary techniques, gives new life to ancient tales and imagines possible futures.
The post Meet the Omnivore: Artist Fires Up NVIDIA Omniverse to Glaze Animated Ceramics appeared first on NVIDIA Blog.
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On August 9, 2022, we announced the general availability of cross-account sharing of Amazon SageMaker Pipelines entities. You can now use cross-account support for Amazon SageMaker Pipelines to share pipeline entities across AWS accounts and access shared pipelines directly through Amazon SageMaker API calls. Customers are increasingly adopting multi-account architectures for deploying and managing machine […]
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Data preparation is the process of collecting, cleaning, and transforming raw data to make it suitable for insight extraction through machine learning (ML) and analytics. Data preparation is crucial for ML and analytics pipelines. Your model and insights will only be as reliable as the data you use for training them. Flawed data will produce […]
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The Metaverse is seen as the fourth wave of computing and networking - the first three being the mainframe, personal computing, and mobile + cloud. Yet, In contrast to the previous waves, the Metaverse adds 3D experience, or immersion.
The post A Comprehensive Definition of the Metaverse appeared first on Data Science Central.
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https://www.youtube.com/watch?v=KJOZEwJ3w0o&ab_channel=JohannezzMusic
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Reptile was developed by open ai and it'll open yo eye🗿
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https://deumbra.com/2022/08/rllib-for-deep-hierarchical-multiagent-reinforcement-learning/
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According to Forbes, data scientists spend about 80% of their time on data collection, cleansing, and preparation, while only 20% of it is left for actual data analysis. Organizations that don’t utilize master data management systems or data warehouses to keep their data clean and accurate end up basing crucial business decisions on bad data. … Read More »Data cleansing for reliable analytics and business intelligence
The post Data cleansing for reliable analytics and business intelligence appeared first on Data Science Central.
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In December 2020, AWS announced the general availability of Amazon SageMaker JumpStart, a capability of Amazon SageMaker that helps you quickly and easily get started with machine learning (ML). JumpStart provides one-click fine-tuning and deployment of a wide variety of pre-trained models across popular ML tasks, as well as a selection of end-to-end solutions that […]
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Organizations in the lending and mortgage industry process thousands of documents on a daily basis. From a new mortgage application to mortgage refinance, these business processes involve hundreds of documents per application. There is limited automation available today to process and extract information from all the documents, especially due to varying formats and layouts. Due […]
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Looking at all of the very large convolutional neural networks such as ResNets, VGGs, and the like, it begs the question on how we can make all of these networks smaller with less parameters while still maintaining the same level of accuracy or even improving generalization of the model using a smaller amount of parameters. […]
The post Using Depthwise Separable Convolutions in Tensorflow appeared first on Machine Learning Mastery.
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Sponsored Post AI & Machine Learning now power most product experiences even beyond those of the big technology companies. Today, your models must perform and function correctly to ultimately deliver business value. The cost of deploying a slow or bad model, or not detecting undesirable behavior quickly, could significantly impact customer experience and the business’ […]
The post Mastering MLOps: Live Model Deployment & Inference Course with Stefan Krawczyk appeared first on Machine Learning Mastery.
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